Overview

Dataset statistics

Number of variables 12
Number of observations 1000
Missing cells 0
Missing cells (%) 0.0%
Duplicate rows 360
Duplicate rows (%) 36.0%
Total size in memory 315.6 KiB
Average record size in memory 323.1 B

Variable types

Numeric 8
Categorical 3
Boolean 1

Alerts

Dataset has 360 (36.0%) duplicate rows Duplicates
5G Capability is highly overall correlated with Market Share (%) and 1 other fields High correlation
Market Share (%) is highly overall correlated with 5G Capability High correlation
Product Model is highly overall correlated with 5G Capability High correlation

Reproduction

Analysis started 2026-02-19 09:52:02.472701
Analysis finished 2026-02-19 09:52:15.624697
Duration 13.15 seconds
Software version ydata-profiling vv4.18.0
Download configuration config.json

Variables

Year
Real number (ℝ)

Distinct 6
Distinct (%) 0.6%
Missing 0
Missing (%) 0.0%
Infinite 0
Infinite (%) 0.0%
Mean 2021.456
Minimum 2019
Maximum 2024
Zeros 0
Zeros (%) 0.0%
Negative 0
Negative (%) 0.0%
Memory size 7.9 KiB
2026-02-19T15:22:15.982903 image/svg+xml Matplotlib v3.8.4, https://matplotlib.org/

Quantile statistics

Minimum 2019
5-th percentile 2019
Q1 2020
median 2021
Q3 2023
95-th percentile 2024
Maximum 2024
Range 5
Interquartile range (IQR) 3

Descriptive statistics

Standard deviation 1.7002808
Coefficient of variation (CV) 0.00084111692
Kurtosis -1.2533538
Mean 2021.456
Median Absolute Deviation (MAD) 1
Skewness 0.025365695
Sum 2021456
Variance 2.890955
Monotonicity Not monotonic
2026-02-19T15:22:16.169867 image/svg+xml Matplotlib v3.8.4, https://matplotlib.org/
Histogram with fixed size bins (bins=6)
Value Count Frequency (%)
2019 173
17.3%
2021 171
17.1%
2022 169
16.9%
2020 166
16.6%
2023 164
16.4%
2024 157
15.7%
Value Count Frequency (%)
2019 173
17.3%
2020 166
16.6%
2021 171
17.1%
2022 169
16.9%
2023 164
16.4%
2024 157
15.7%
Value Count Frequency (%)
2024 157
15.7%
2023 164
16.4%
2022 169
16.9%
2021 171
17.1%
2020 166
16.6%
2019 173
17.3%

Quarter
Categorical

Distinct 4
Distinct (%) 0.4%
Missing 0
Missing (%) 0.0%
Memory size 57.7 KiB
Q1
256 
Q2
255 
Q3
248 
Q4
241 

Length

Max length 2
Median length 2
Mean length 2
Min length 2

Characters and Unicode

Total characters 2000
Distinct characters 5
Distinct categories 1 ?
Distinct scripts 1 ?
Distinct blocks 1 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique 0 ?
Unique (%) 0.0%

Sample

1st row Q1
2nd row Q1
3rd row Q1
4th row Q1
5th row Q1

Common Values

Value Count Frequency (%)
Q1 256
25.6%
Q2 255
25.5%
Q3 248
24.8%
Q4 241
24.1%

Length

2026-02-19T15:22:16.372844 image/svg+xml Matplotlib v3.8.4, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2026-02-19T15:22:16.573355 image/svg+xml Matplotlib v3.8.4, https://matplotlib.org/
Value Count Frequency (%)
q1 256
25.6%
q2 255
25.5%
q3 248
24.8%
q4 241
24.1%

Most occurring characters

Value Count Frequency (%)
Q 1000
50.0%
1 256
 
12.8%
2 255
 
12.8%
3 248
 
12.4%
4 241
 
12.0%

Most occurring categories

Value Count Frequency (%)
(unknown) 2000
100.0%

Most frequent character per category

(unknown)
Value Count Frequency (%)
Q 1000
50.0%
1 256
 
12.8%
2 255
 
12.8%
3 248
 
12.4%
4 241
 
12.0%

Most occurring scripts

Value Count Frequency (%)
(unknown) 2000
100.0%

Most frequent character per script

(unknown)
Value Count Frequency (%)
Q 1000
50.0%
1 256
 
12.8%
2 255
 
12.8%
3 248
 
12.4%
4 241
 
12.0%

Most occurring blocks

Value Count Frequency (%)
(unknown) 2000
100.0%

Most frequent character per block

(unknown)
Value Count Frequency (%)
Q 1000
50.0%
1 256
 
12.8%
2 255
 
12.8%
3 248
 
12.4%
4 241
 
12.0%

Product Model
Categorical

High correlation 

Distinct 15
Distinct (%) 1.5%
Missing 0
Missing (%) 0.0%
Memory size 69.0 KiB
Galaxy S22 5G
79 
Galaxy Note10
74 
Galaxy A32 5G
69 
Galaxy Z Flip3 5G
69 
Galaxy Z Fold3 5G
69 
Other values (10)
640 

Length

Max length 17
Median length 13
Mean length 13.477
Min length 10

Characters and Unicode

Total characters 13477
Distinct characters 24
Distinct categories 1 ?
Distinct scripts 1 ?
Distinct blocks 1 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique 0 ?
Unique (%) 0.0%

Sample

1st row Galaxy S10
2nd row Galaxy Note10
3rd row Galaxy S20
4th row Galaxy Note20
5th row Galaxy S21

Common Values

Value Count Frequency (%)
Galaxy S22 5G 79
 
7.9%
Galaxy Note10 74
 
7.4%
Galaxy A32 5G 69
 
6.9%
Galaxy Z Flip3 5G 69
 
6.9%
Galaxy Z Fold3 5G 69
 
6.9%
Galaxy A52 5G 68
 
6.8%
Galaxy Note20 67
 
6.7%
Galaxy S21 67
 
6.7%
Galaxy S10 66
 
6.6%
Galaxy A73 5G 66
 
6.6%
Other values (5) 306
30.6%

Length

2026-02-19T15:22:16.783402 image/svg+xml Matplotlib v3.8.4, https://matplotlib.org/
Histogram of lengths of the category
Value Count Frequency (%)
galaxy 1000
34.1%
5g 666
22.7%
z 264
 
9.0%
s22 79
 
2.7%
note10 74
 
2.5%
a32 69
 
2.4%
flip3 69
 
2.4%
fold3 69
 
2.4%
a52 68
 
2.3%
s21 67
 
2.3%
Other values (8) 505
17.2%

Most occurring characters

Value Count Frequency (%)
a 2000
14.8%
1930
14.3%
G 1666
12.4%
l 1264
9.4%
x 1000
 
7.4%
y 1000
 
7.4%
5 796
 
5.9%
2 611
 
4.5%
3 331
 
2.5%
S 330
 
2.4%
Other values (14) 2549
18.9%

Most occurring categories

Value Count Frequency (%)
(unknown) 13477
100.0%

Most frequent character per category

(unknown)
Value Count Frequency (%)
a 2000
14.8%
1930
14.3%
G 1666
12.4%
l 1264
9.4%
x 1000
 
7.4%
y 1000
 
7.4%
5 796
 
5.9%
2 611
 
4.5%
3 331
 
2.5%
S 330
 
2.4%
Other values (14) 2549
18.9%

Most occurring scripts

Value Count Frequency (%)
(unknown) 13477
100.0%

Most frequent character per script

(unknown)
Value Count Frequency (%)
a 2000
14.8%
1930
14.3%
G 1666
12.4%
l 1264
9.4%
x 1000
 
7.4%
y 1000
 
7.4%
5 796
 
5.9%
2 611
 
4.5%
3 331
 
2.5%
S 330
 
2.4%
Other values (14) 2549
18.9%

Most occurring blocks

Value Count Frequency (%)
(unknown) 13477
100.0%

Most frequent character per block

(unknown)
Value Count Frequency (%)
a 2000
14.8%
1930
14.3%
G 1666
12.4%
l 1264
9.4%
x 1000
 
7.4%
y 1000
 
7.4%
5 796
 
5.9%
2 611
 
4.5%
3 331
 
2.5%
S 330
 
2.4%
Other values (14) 2549
18.9%

5G Capability
Boolean

High correlation 

Distinct 2
Distinct (%) 0.2%
Missing 0
Missing (%) 0.0%
Memory size 1.1 KiB
True
666 
False
334 
Value Count Frequency (%)
True 666
66.6%
False 334
33.4%
2026-02-19T15:22:16.964174 image/svg+xml Matplotlib v3.8.4, https://matplotlib.org/

Units Sold
Real number (ℝ)

Distinct 354
Distinct (%) 35.4%
Missing 0
Missing (%) 0.0%
Infinite 0
Infinite (%) 0.0%
Mean 32842.99
Minimum 5309
Maximum 64883
Zeros 0
Zeros (%) 0.0%
Negative 0
Negative (%) 0.0%
Memory size 7.9 KiB
2026-02-19T15:22:17.171373 image/svg+xml Matplotlib v3.8.4, https://matplotlib.org/

Quantile statistics

Minimum 5309
5-th percentile 7473
Q1 19327.25
median 33689
Q3 43911
95-th percentile 58340.25
Maximum 64883
Range 59574
Interquartile range (IQR) 24583.75

Descriptive statistics

Standard deviation 16039.771
Coefficient of variation (CV) 0.48837729
Kurtosis -0.95610633
Mean 32842.99
Median Absolute Deviation (MAD) 12477
Skewness 0.040410034
Sum 32842990
Variance 2.5727424 × 108
Monotonicity Not monotonic
2026-02-19T15:22:17.431161 image/svg+xml Matplotlib v3.8.4, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
Value Count Frequency (%)
38119 6
 
0.6%
5465 6
 
0.6%
42266 6
 
0.6%
36255 6
 
0.6%
26634 5
 
0.5%
42820 5
 
0.5%
15007 5
 
0.5%
40418 5
 
0.5%
8330 5
 
0.5%
36216 5
 
0.5%
Other values (344) 946
94.6%
Value Count Frequency (%)
5309 2
 
0.2%
5465 6
0.6%
5564 2
 
0.2%
5718 2
 
0.2%
6501 2
 
0.2%
6542 3
0.3%
6548 3
0.3%
6557 2
 
0.2%
6628 4
0.4%
6719 3
0.3%
Value Count Frequency (%)
64883 3
0.3%
64381 2
0.2%
63974 3
0.3%
63966 3
0.3%
63804 2
0.2%
63494 2
0.2%
63137 4
0.4%
62968 3
0.3%
62215 2
0.2%
61958 2
0.2%

Revenue ($)
Real number (ℝ)

Distinct 360
Distinct (%) 36.0%
Missing 0
Missing (%) 0.0%
Infinite 0
Infinite (%) 0.0%
Mean 30197332
Minimum 2987436.4
Maximum 84264944
Zeros 0
Zeros (%) 0.0%
Negative 0
Negative (%) 0.0%
Memory size 7.9 KiB
2026-02-19T15:22:17.695816 image/svg+xml Matplotlib v3.8.4, https://matplotlib.org/

Quantile statistics

Minimum 2987436.4
5-th percentile 6397386.2
Q1 14607494
median 28012005
Q3 41803911
95-th percentile 65444721
Maximum 84264944
Range 81277507
Interquartile range (IQR) 27196417

Descriptive statistics

Standard deviation 18379406
Coefficient of variation (CV) 0.60864339
Kurtosis -0.21298281
Mean 30197332
Median Absolute Deviation (MAD) 13615176
Skewness 0.68631469
Sum 3.0197332 × 1010
Variance 3.3780258 × 1014
Monotonicity Not monotonic
2026-02-19T15:22:17.966867 image/svg+xml Matplotlib v3.8.4, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
Value Count Frequency (%)
14185149.88 6
 
0.6%
49899540.8 6
 
0.6%
12091673.94 6
 
0.6%
35842354.88 5
 
0.5%
33782555.28 5
 
0.5%
63070767.79 5
 
0.5%
45919818.68 5
 
0.5%
56176071.66 5
 
0.5%
17977115.15 5
 
0.5%
19621770.61 5
 
0.5%
Other values (350) 947
94.7%
Value Count Frequency (%)
2987436.384 2
0.2%
4212951.048 3
0.3%
4252116.888 2
0.2%
4424999.499 2
0.2%
4494602.493 3
0.3%
4828393.062 4
0.4%
4874859.738 3
0.3%
4967036.616 2
0.2%
5030391.84 2
0.2%
5136019.542 4
0.4%
Value Count Frequency (%)
84264943.84 2
0.2%
82025137.2 2
0.2%
80946999.25 3
0.3%
79592293.16 3
0.3%
79207664.34 4
0.4%
78970161.31 2
0.2%
76740547.76 2
0.2%
75369161.28 2
0.2%
71988709.97 2
0.2%
71564619.92 3
0.3%

Market Share (%)
Real number (ℝ)

High correlation 

Distinct 274
Distinct (%) 27.4%
Missing 0
Missing (%) 0.0%
Infinite 0
Infinite (%) 0.0%
Mean 3.72357
Minimum -0.49
Maximum 6.95
Zeros 2
Zeros (%) 0.2%
Negative 49
Negative (%) 4.9%
Memory size 7.9 KiB
2026-02-19T15:22:18.226148 image/svg+xml Matplotlib v3.8.4, https://matplotlib.org/

Quantile statistics

Minimum -0.49
5-th percentile 0
Q1 2.635
median 3.76
Q3 5.2825
95-th percentile 6.65
Maximum 6.95
Range 7.44
Interquartile range (IQR) 2.6475

Descriptive statistics

Standard deviation 1.9911085
Coefficient of variation (CV) 0.53473104
Kurtosis -0.7364446
Mean 3.72357
Median Absolute Deviation (MAD) 1.31
Skewness -0.31978569
Sum 3723.57
Variance 3.9645129
Monotonicity Not monotonic
2026-02-19T15:22:18.744644 image/svg+xml Matplotlib v3.8.4, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
Value Count Frequency (%)
6.02 13
 
1.3%
0.34 13
 
1.3%
3.88 12
 
1.2%
4.21 12
 
1.2%
3.44 11
 
1.1%
6.33 11
 
1.1%
4.66 9
 
0.9%
5.28 8
 
0.8%
6.1 8
 
0.8%
3.84 8
 
0.8%
Other values (264) 895
89.5%
Value Count Frequency (%)
-0.49 2
 
0.2%
-0.47 3
0.3%
-0.42 2
 
0.2%
-0.39 2
 
0.2%
-0.36 3
0.3%
-0.35 2
 
0.2%
-0.25 5
0.5%
-0.23 3
0.3%
-0.2 4
0.4%
-0.17 2
 
0.2%
Value Count Frequency (%)
6.95 3
0.3%
6.92 4
0.4%
6.91 5
0.5%
6.84 6
0.6%
6.83 7
0.7%
6.82 3
0.3%
6.81 5
0.5%
6.75 3
0.3%
6.71 6
0.6%
6.7 2
 
0.2%

Regional 5G Coverage (%)
Real number (ℝ)

Distinct 344
Distinct (%) 34.4%
Missing 0
Missing (%) 0.0%
Infinite 0
Infinite (%) 0.0%
Mean 66.88972
Minimum 25.34
Maximum 103.92
Zeros 0
Zeros (%) 0.0%
Negative 0
Negative (%) 0.0%
Memory size 7.9 KiB
2026-02-19T15:22:18.994078 image/svg+xml Matplotlib v3.8.4, https://matplotlib.org/

Quantile statistics

Minimum 25.34
5-th percentile 38.79
Q1 50.4
median 67.05
Q3 83.21
95-th percentile 98.2245
Maximum 103.92
Range 78.58
Interquartile range (IQR) 32.81

Descriptive statistics

Standard deviation 19.254095
Coefficient of variation (CV) 0.28784834
Kurtosis -0.95536163
Mean 66.88972
Median Absolute Deviation (MAD) 16.42
Skewness 0.018700315
Sum 66889.72
Variance 370.72016
Monotonicity Not monotonic
2026-02-19T15:22:19.245941 image/svg+xml Matplotlib v3.8.4, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
Value Count Frequency (%)
83.96 10
 
1.0%
69.32 8
 
0.8%
33.54 8
 
0.8%
87.83 7
 
0.7%
74.46 7
 
0.7%
48.75 7
 
0.7%
73.54 6
 
0.6%
75.22 6
 
0.6%
47.84 6
 
0.6%
67 6
 
0.6%
Other values (334) 929
92.9%
Value Count Frequency (%)
25.34 2
0.2%
25.7 3
0.3%
25.88 3
0.3%
27.27 3
0.3%
27.94 3
0.3%
28.49 3
0.3%
30.32 4
0.4%
30.37 3
0.3%
31.64 2
0.2%
32.09 2
0.2%
Value Count Frequency (%)
103.92 2
0.2%
103.82 2
0.2%
103.78 3
0.3%
103.73 3
0.3%
103.57 3
0.3%
102.8 2
0.2%
102.54 2
0.2%
102.49 2
0.2%
102.38 2
0.2%
101.8 3
0.3%

5G Subscribers (millions)
Real number (ℝ)

Distinct 350
Distinct (%) 35.0%
Missing 0
Missing (%) 0.0%
Infinite 0
Infinite (%) 0.0%
Mean 30.15208
Minimum -0.89
Maximum 54.94
Zeros 0
Zeros (%) 0.0%
Negative 10
Negative (%) 1.0%
Memory size 7.9 KiB
2026-02-19T15:22:19.478900 image/svg+xml Matplotlib v3.8.4, https://matplotlib.org/

Quantile statistics

Minimum -0.89
5-th percentile 6.712
Q1 18.4125
median 29.915
Q3 44.36
95-th percentile 51.8
Maximum 54.94
Range 55.83
Interquartile range (IQR) 25.9475

Descriptive statistics

Standard deviation 14.537781
Coefficient of variation (CV) 0.48214853
Kurtosis -1.0357426
Mean 30.15208
Median Absolute Deviation (MAD) 13.01
Skewness -0.1497599
Sum 30152.08
Variance 211.34708
Monotonicity Not monotonic
2026-02-19T15:22:19.726350 image/svg+xml Matplotlib v3.8.4, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
Value Count Frequency (%)
29.96 9
 
0.9%
23.96 7
 
0.7%
48.17 7
 
0.7%
13.99 6
 
0.6%
45.99 6
 
0.6%
8.11 6
 
0.6%
38.33 6
 
0.6%
9.77 6
 
0.6%
13.22 5
 
0.5%
24.69 5
 
0.5%
Other values (340) 937
93.7%
Value Count Frequency (%)
-0.89 2
 
0.2%
-0.65 4
0.4%
-0.05 4
0.4%
0.34 3
0.3%
0.84 2
 
0.2%
1.47 3
0.3%
1.57 3
0.3%
1.68 3
0.3%
2.27 2
 
0.2%
2.53 5
0.5%
Value Count Frequency (%)
54.94 3
0.3%
54.48 2
0.2%
54.35 2
0.2%
54.21 4
0.4%
53.76 2
0.2%
53.48 2
0.2%
53.4 2
0.2%
53.26 2
0.2%
52.82 2
0.2%
52.81 2
0.2%

Avg 5G Speed (Mbps)
Real number (ℝ)

Distinct 358
Distinct (%) 35.8%
Missing 0
Missing (%) 0.0%
Infinite 0
Infinite (%) 0.0%
Mean 179.22556
Minimum 50.37
Maximum 298.7
Zeros 0
Zeros (%) 0.0%
Negative 0
Negative (%) 0.0%
Memory size 7.9 KiB
2026-02-19T15:22:19.968074 image/svg+xml Matplotlib v3.8.4, https://matplotlib.org/

Quantile statistics

Minimum 50.37
5-th percentile 67.46
Q1 120.41
median 177.39
Q3 238.86
95-th percentile 287.88
Maximum 298.7
Range 248.33
Interquartile range (IQR) 118.45

Descriptive statistics

Standard deviation 70.470934
Coefficient of variation (CV) 0.39319689
Kurtosis -1.1146455
Mean 179.22556
Median Absolute Deviation (MAD) 59.22
Skewness -0.018571924
Sum 179225.56
Variance 4966.1525
Monotonicity Not monotonic
2026-02-19T15:22:20.229856 image/svg+xml Matplotlib v3.8.4, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
Value Count Frequency (%)
292.18 6
 
0.6%
284.33 6
 
0.6%
81.43 6
 
0.6%
238.86 5
 
0.5%
162.28 5
 
0.5%
160.98 5
 
0.5%
85.44 5
 
0.5%
175.6 5
 
0.5%
177.43 5
 
0.5%
66.34 5
 
0.5%
Other values (348) 947
94.7%
Value Count Frequency (%)
50.37 2
0.2%
51.12 2
0.2%
51.73 3
0.3%
52.28 2
0.2%
52.52 3
0.3%
52.85 3
0.3%
54.56 2
0.2%
57.25 2
0.2%
57.27 3
0.3%
58.21 2
0.2%
Value Count Frequency (%)
298.7 2
0.2%
297.81 2
0.2%
297.3 2
0.2%
296.75 2
0.2%
296.12 2
0.2%
295.85 2
0.2%
295.62 2
0.2%
294.91 3
0.3%
294.86 3
0.3%
294.81 3
0.3%

Preference for 5G (%)
Real number (ℝ)

Distinct 347
Distinct (%) 34.7%
Missing 0
Missing (%) 0.0%
Infinite 0
Infinite (%) 0.0%
Mean 67.14291
Minimum 37.14
Maximum 94.84
Zeros 0
Zeros (%) 0.0%
Negative 0
Negative (%) 0.0%
Memory size 7.9 KiB
2026-02-19T15:22:20.455616 image/svg+xml Matplotlib v3.8.4, https://matplotlib.org/

Quantile statistics

Minimum 37.14
5-th percentile 43.46
Q1 53.2675
median 66.96
Q3 80.99
95-th percentile 91.7235
Maximum 94.84
Range 57.7
Interquartile range (IQR) 27.7225

Descriptive statistics

Standard deviation 15.75925
Coefficient of variation (CV) 0.23471206
Kurtosis -1.208542
Mean 67.14291
Median Absolute Deviation (MAD) 14
Skewness -0.00061770557
Sum 67142.91
Variance 248.35398
Monotonicity Not monotonic
2026-02-19T15:22:20.713460 image/svg+xml Matplotlib v3.8.4, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
Value Count Frequency (%)
63.04 7
 
0.7%
88.16 7
 
0.7%
87.01 6
 
0.6%
84.08 6
 
0.6%
86.82 6
 
0.6%
37.14 6
 
0.6%
85.88 6
 
0.6%
63.86 5
 
0.5%
59.6 5
 
0.5%
75.51 5
 
0.5%
Other values (337) 941
94.1%
Value Count Frequency (%)
37.14 6
0.6%
37.26 5
0.5%
38.07 2
 
0.2%
38.28 3
0.3%
38.5 2
 
0.2%
39.33 4
0.4%
39.57 2
 
0.2%
40.03 3
0.3%
40.12 2
 
0.2%
41.31 2
 
0.2%
Value Count Frequency (%)
94.84 2
0.2%
94.7 2
0.2%
94.43 4
0.4%
94.36 3
0.3%
94.16 3
0.3%
93.45 4
0.4%
93.38 3
0.3%
93.28 3
0.3%
93.25 2
0.2%
93.2 3
0.3%

Region
Categorical

Distinct 5
Distinct (%) 0.5%
Missing 0
Missing (%) 0.0%
Memory size 68.4 KiB
North America
226 
Latin America
205 
Middle East & Africa
200 
Europe
192 
Asia-Pacific
177 

Length

Max length 20
Median length 13
Mean length 12.879
Min length 6

Characters and Unicode

Total characters 12879
Distinct characters 25
Distinct categories 1 ?
Distinct scripts 1 ?
Distinct blocks 1 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique 0 ?
Unique (%) 0.0%

Sample

1st row Asia-Pacific
2nd row Latin America
3rd row Middle East & Africa
4th row North America
5th row Latin America

Common Values

Value Count Frequency (%)
North America 226
22.6%
Latin America 205
20.5%
Middle East & Africa 200
20.0%
Europe 192
19.2%
Asia-Pacific 177
17.7%

Length

2026-02-19T15:22:20.941782 image/svg+xml Matplotlib v3.8.4, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2026-02-19T15:22:21.143089 image/svg+xml Matplotlib v3.8.4, https://matplotlib.org/
Value Count Frequency (%)
america 431
21.2%
north 226
11.1%
latin 205
10.1%
middle 200
9.8%
east 200
9.8%
200
9.8%
africa 200
9.8%
europe 192
9.5%
asia-pacific 177
8.7%

Most occurring characters

Value Count Frequency (%)
i 1567
12.2%
a 1390
 
10.8%
r 1049
 
8.1%
1031
 
8.0%
c 985
 
7.6%
e 823
 
6.4%
A 808
 
6.3%
t 631
 
4.9%
m 431
 
3.3%
o 418
 
3.2%
Other values (15) 3746
29.1%

Most occurring categories

Value Count Frequency (%)
(unknown) 12879
100.0%

Most frequent character per category

(unknown)
Value Count Frequency (%)
i 1567
12.2%
a 1390
 
10.8%
r 1049
 
8.1%
1031
 
8.0%
c 985
 
7.6%
e 823
 
6.4%
A 808
 
6.3%
t 631
 
4.9%
m 431
 
3.3%
o 418
 
3.2%
Other values (15) 3746
29.1%

Most occurring scripts

Value Count Frequency (%)
(unknown) 12879
100.0%

Most frequent character per script

(unknown)
Value Count Frequency (%)
i 1567
12.2%
a 1390
 
10.8%
r 1049
 
8.1%
1031
 
8.0%
c 985
 
7.6%
e 823
 
6.4%
A 808
 
6.3%
t 631
 
4.9%
m 431
 
3.3%
o 418
 
3.2%
Other values (15) 3746
29.1%

Most occurring blocks

Value Count Frequency (%)
(unknown) 12879
100.0%

Most frequent character per block

(unknown)
Value Count Frequency (%)
i 1567
12.2%
a 1390
 
10.8%
r 1049
 
8.1%
1031
 
8.0%
c 985
 
7.6%
e 823
 
6.4%
A 808
 
6.3%
t 631
 
4.9%
m 431
 
3.3%
o 418
 
3.2%
Other values (15) 3746
29.1%

Interactions

2026-02-19T15:22:13.578728 image/svg+xml Matplotlib v3.8.4, https://matplotlib.org/
2026-02-19T15:22:03.247479 image/svg+xml Matplotlib v3.8.4, https://matplotlib.org/
2026-02-19T15:22:04.641018 image/svg+xml Matplotlib v3.8.4, https://matplotlib.org/
2026-02-19T15:22:06.121842 image/svg+xml Matplotlib v3.8.4, https://matplotlib.org/
2026-02-19T15:22:07.629399 image/svg+xml Matplotlib v3.8.4, https://matplotlib.org/
2026-02-19T15:22:09.216510 image/svg+xml Matplotlib v3.8.4, https://matplotlib.org/
2026-02-19T15:22:10.650277 image/svg+xml Matplotlib v3.8.4, https://matplotlib.org/
2026-02-19T15:22:12.102887 image/svg+xml Matplotlib v3.8.4, https://matplotlib.org/
2026-02-19T15:22:13.753664 image/svg+xml Matplotlib v3.8.4, https://matplotlib.org/
2026-02-19T15:22:03.439647 image/svg+xml Matplotlib v3.8.4, https://matplotlib.org/
2026-02-19T15:22:04.818675 image/svg+xml Matplotlib v3.8.4, https://matplotlib.org/
2026-02-19T15:22:06.295706 image/svg+xml Matplotlib v3.8.4, https://matplotlib.org/
2026-02-19T15:22:07.815261 image/svg+xml Matplotlib v3.8.4, https://matplotlib.org/
2026-02-19T15:22:09.387849 image/svg+xml Matplotlib v3.8.4, https://matplotlib.org/
2026-02-19T15:22:10.811205 image/svg+xml Matplotlib v3.8.4, https://matplotlib.org/
2026-02-19T15:22:12.278430 image/svg+xml Matplotlib v3.8.4, https://matplotlib.org/
2026-02-19T15:22:13.926724 image/svg+xml Matplotlib v3.8.4, https://matplotlib.org/
2026-02-19T15:22:03.612263 image/svg+xml Matplotlib v3.8.4, https://matplotlib.org/
2026-02-19T15:22:04.983444 image/svg+xml Matplotlib v3.8.4, https://matplotlib.org/
2026-02-19T15:22:06.472309 image/svg+xml Matplotlib v3.8.4, https://matplotlib.org/
2026-02-19T15:22:07.983818 image/svg+xml Matplotlib v3.8.4, https://matplotlib.org/
2026-02-19T15:22:09.566814 image/svg+xml Matplotlib v3.8.4, https://matplotlib.org/
2026-02-19T15:22:10.989786 image/svg+xml Matplotlib v3.8.4, https://matplotlib.org/
2026-02-19T15:22:12.449511 image/svg+xml Matplotlib v3.8.4, https://matplotlib.org/
2026-02-19T15:22:14.127786 image/svg+xml Matplotlib v3.8.4, https://matplotlib.org/
2026-02-19T15:22:03.784883 image/svg+xml Matplotlib v3.8.4, https://matplotlib.org/
2026-02-19T15:22:05.181267 image/svg+xml Matplotlib v3.8.4, https://matplotlib.org/
2026-02-19T15:22:06.728678 image/svg+xml Matplotlib v3.8.4, https://matplotlib.org/
2026-02-19T15:22:08.162019 image/svg+xml Matplotlib v3.8.4, https://matplotlib.org/
2026-02-19T15:22:09.747364 image/svg+xml Matplotlib v3.8.4, https://matplotlib.org/
2026-02-19T15:22:11.190983 image/svg+xml Matplotlib v3.8.4, https://matplotlib.org/
2026-02-19T15:22:12.657920 image/svg+xml Matplotlib v3.8.4, https://matplotlib.org/
2026-02-19T15:22:14.307261 image/svg+xml Matplotlib v3.8.4, https://matplotlib.org/
2026-02-19T15:22:03.949560 image/svg+xml Matplotlib v3.8.4, https://matplotlib.org/
2026-02-19T15:22:05.361355 image/svg+xml Matplotlib v3.8.4, https://matplotlib.org/
2026-02-19T15:22:06.907686 image/svg+xml Matplotlib v3.8.4, https://matplotlib.org/
2026-02-19T15:22:08.331202 image/svg+xml Matplotlib v3.8.4, https://matplotlib.org/
2026-02-19T15:22:09.930283 image/svg+xml Matplotlib v3.8.4, https://matplotlib.org/
2026-02-19T15:22:11.373736 image/svg+xml Matplotlib v3.8.4, https://matplotlib.org/
2026-02-19T15:22:12.840706 image/svg+xml Matplotlib v3.8.4, https://matplotlib.org/
2026-02-19T15:22:14.491557 image/svg+xml Matplotlib v3.8.4, https://matplotlib.org/
2026-02-19T15:22:04.135298 image/svg+xml Matplotlib v3.8.4, https://matplotlib.org/
2026-02-19T15:22:05.578189 image/svg+xml Matplotlib v3.8.4, https://matplotlib.org/
2026-02-19T15:22:07.102612 image/svg+xml Matplotlib v3.8.4, https://matplotlib.org/
2026-02-19T15:22:08.523745 image/svg+xml Matplotlib v3.8.4, https://matplotlib.org/
2026-02-19T15:22:10.113328 image/svg+xml Matplotlib v3.8.4, https://matplotlib.org/
2026-02-19T15:22:11.580930 image/svg+xml Matplotlib v3.8.4, https://matplotlib.org/
2026-02-19T15:22:13.045865 image/svg+xml Matplotlib v3.8.4, https://matplotlib.org/
2026-02-19T15:22:14.681501 image/svg+xml Matplotlib v3.8.4, https://matplotlib.org/
2026-02-19T15:22:04.299669 image/svg+xml Matplotlib v3.8.4, https://matplotlib.org/
2026-02-19T15:22:05.744559 image/svg+xml Matplotlib v3.8.4, https://matplotlib.org/
2026-02-19T15:22:07.276786 image/svg+xml Matplotlib v3.8.4, https://matplotlib.org/
2026-02-19T15:22:08.690221 image/svg+xml Matplotlib v3.8.4, https://matplotlib.org/
2026-02-19T15:22:10.290289 image/svg+xml Matplotlib v3.8.4, https://matplotlib.org/
2026-02-19T15:22:11.751022 image/svg+xml Matplotlib v3.8.4, https://matplotlib.org/
2026-02-19T15:22:13.223219 image/svg+xml Matplotlib v3.8.4, https://matplotlib.org/
2026-02-19T15:22:14.858943 image/svg+xml Matplotlib v3.8.4, https://matplotlib.org/
2026-02-19T15:22:04.477853 image/svg+xml Matplotlib v3.8.4, https://matplotlib.org/
2026-02-19T15:22:05.925111 image/svg+xml Matplotlib v3.8.4, https://matplotlib.org/
2026-02-19T15:22:07.457603 image/svg+xml Matplotlib v3.8.4, https://matplotlib.org/
2026-02-19T15:22:08.858007 image/svg+xml Matplotlib v3.8.4, https://matplotlib.org/
2026-02-19T15:22:10.479510 image/svg+xml Matplotlib v3.8.4, https://matplotlib.org/
2026-02-19T15:22:11.924722 image/svg+xml Matplotlib v3.8.4, https://matplotlib.org/
2026-02-19T15:22:13.396114 image/svg+xml Matplotlib v3.8.4, https://matplotlib.org/

Correlations

2026-02-19T15:22:21.338142 image/svg+xml Matplotlib v3.8.4, https://matplotlib.org/
5G Capability 5G Subscribers (millions) Avg 5G Speed (Mbps) Market Share (%) Preference for 5G (%) Product Model Quarter Region Regional 5G Coverage (%) Revenue ($) Units Sold Year
5G Capability 1.000 0.362 0.089 0.798 0.396 0.993 0.000 0.054 0.412 0.287 0.348 0.000
5G Subscribers (millions) 0.362 1.000 0.096 0.172 0.045 0.223 0.146 0.126 0.139 0.083 0.091 -0.023
Avg 5G Speed (Mbps) 0.089 0.096 1.000 0.009 -0.029 0.166 0.104 0.119 0.046 0.131 0.030 0.131
Market Share (%) 0.798 0.172 0.009 1.000 0.246 0.290 0.090 0.147 0.176 0.160 0.120 0.019
Preference for 5G (%) 0.396 0.045 -0.029 0.246 1.000 0.240 0.105 0.133 0.020 0.161 0.060 -0.071
Product Model 0.993 0.223 0.166 0.290 0.240 1.000 0.000 0.170 0.225 0.183 0.214 0.000
Quarter 0.000 0.146 0.104 0.090 0.105 0.000 1.000 0.073 0.127 0.110 0.151 0.000
Region 0.054 0.126 0.119 0.147 0.133 0.170 0.073 1.000 0.115 0.151 0.135 0.059
Regional 5G Coverage (%) 0.412 0.139 0.046 0.176 0.020 0.225 0.127 0.115 1.000 0.095 0.091 0.069
Revenue ($) 0.287 0.083 0.131 0.160 0.161 0.183 0.110 0.151 0.095 1.000 0.051 -0.044
Units Sold 0.348 0.091 0.030 0.120 0.060 0.214 0.151 0.135 0.091 0.051 1.000 0.000
Year 0.000 -0.023 0.131 0.019 -0.071 0.000 0.000 0.059 0.069 -0.044 0.000 1.000

Missing values

2026-02-19T15:22:15.139055 image/svg+xml Matplotlib v3.8.4, https://matplotlib.org/
A simple visualization of nullity by column.
2026-02-19T15:22:15.462054 image/svg+xml Matplotlib v3.8.4, https://matplotlib.org/
Nullity matrix is a data-dense display which lets you quickly visually pick out patterns in data completion.

Sample

Year Quarter Product Model 5G Capability Units Sold Revenue ($) Market Share (%) Regional 5G Coverage (%) 5G Subscribers (millions) Avg 5G Speed (Mbps) Preference for 5G (%) Region
0 2019 Q1 Galaxy S10 No 26396 4.212951e+06 1.04 57.36 39.55 293.10 55.87 Asia-Pacific
1 2019 Q1 Galaxy Note10 No 25671 7.240266e+06 2.82 85.80 42.58 67.46 37.26 Latin America
2 2019 Q1 Galaxy S20 No 16573 2.560833e+07 -0.03 47.02 3.78 77.25 84.66 Middle East & Africa
3 2019 Q1 Galaxy Note20 No 7177 2.198442e+07 0.84 25.70 23.41 105.27 40.03 North America
4 2019 Q1 Galaxy S21 No 45633 1.634244e+07 2.36 89.13 44.43 206.17 76.88 Latin America
5 2019 Q1 Galaxy A32 5G Yes 15912 1.717833e+07 5.41 59.12 12.14 179.15 80.79 Middle East & Africa
6 2019 Q1 Galaxy A52 5G Yes 7231 4.863981e+07 5.90 52.94 44.36 259.16 77.55 Latin America
7 2019 Q1 Galaxy A73 5G Yes 58711 7.017578e+07 4.92 79.95 49.70 191.42 74.83 Europe
8 2019 Q1 Galaxy Z Fold2 5G Yes 40641 5.195956e+07 2.64 44.77 31.27 151.18 66.51 North America
9 2019 Q1 Galaxy Z Flip3 5G Yes 38119 4.989954e+07 6.84 51.21 38.33 284.33 87.01 Latin America
Year Quarter Product Model 5G Capability Units Sold Revenue ($) Market Share (%) Regional 5G Coverage (%) 5G Subscribers (millions) Avg 5G Speed (Mbps) Preference for 5G (%) Region
990 2020 Q1 Galaxy A32 5G Yes 42883 1.858873e+07 6.37 72.87 45.86 273.59 52.90 Asia-Pacific
991 2023 Q1 Galaxy Z Flip5 5G Yes 11658 1.413069e+07 4.81 64.15 50.51 117.92 62.56 Europe
992 2020 Q1 Galaxy S22 5G Yes 40807 2.840947e+07 3.04 47.56 33.59 95.38 57.91 Latin America
993 2019 Q4 Galaxy Z Flip3 5G Yes 34541 2.330878e+07 4.03 59.35 8.37 138.67 80.35 Latin America
994 2019 Q4 Galaxy S22 5G Yes 6719 3.831129e+07 5.38 42.55 50.32 110.97 87.80 Asia-Pacific
995 2023 Q4 Galaxy S22 5G Yes 36216 2.995937e+07 3.82 70.59 46.92 177.43 63.86 Latin America
996 2022 Q2 Galaxy S21 No 33806 2.369938e+07 -0.23 77.31 47.51 129.70 78.41 North America
997 2022 Q1 Galaxy S10 No 23678 2.330203e+07 0.58 45.61 43.79 156.56 72.06 Europe
998 2023 Q4 Galaxy Note10 No 35697 1.946256e+07 2.49 36.55 36.44 236.39 47.11 North America
999 2020 Q4 Galaxy Note20 No 7473 1.962177e+07 3.88 74.66 27.55 177.22 72.36 North America

Duplicate rows

Most frequently occurring

Year Quarter Product Model 5G Capability Units Sold Revenue ($) Market Share (%) Regional 5G Coverage (%) 5G Subscribers (millions) Avg 5G Speed (Mbps) Preference for 5G (%) Region # duplicates
9 2019 Q1 Galaxy S22 5G Yes 36255 1.209167e+07 4.66 56.50 9.77 81.43 85.88 Middle East & Africa 6
11 2019 Q1 Galaxy Z Flip3 5G Yes 38119 4.989954e+07 6.84 51.21 38.33 284.33 87.01 Latin America 6
199 2022 Q2 Galaxy Note10 No 5465 1.418515e+07 1.97 73.54 45.99 292.18 37.14 North America 6
4 2019 Q1 Galaxy Note10 No 25671 7.240266e+06 2.82 85.80 42.58 67.46 37.26 Latin America 5
25 2019 Q2 Galaxy S23 5G Yes 36613 6.307077e+07 3.25 83.96 13.22 280.73 75.51 North America 5
110 2020 Q4 Galaxy Note20 No 7473 1.962177e+07 3.88 74.66 27.55 177.22 72.36 North America 5
125 2021 Q1 Galaxy Note20 No 36476 9.769649e+06 0.40 67.05 29.96 138.12 52.54 Europe 5
135 2021 Q2 Galaxy A14 5G Yes 33576 1.575834e+07 6.65 73.37 14.85 69.65 58.52 Europe 5
136 2021 Q2 Galaxy A32 5G Yes 26634 1.797712e+07 2.97 45.93 52.08 238.86 74.08 Middle East & Africa 5
156 2021 Q3 Galaxy S10 No 39031 1.860894e+07 3.81 33.54 15.30 107.98 58.30 Asia-Pacific 5